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NASA NTRS2011

Climate Change Impact Uncertainties for Maize in Panama: Farm Information, Climate Projections, and Yield Sensitivities

We present results from a pilot project to characterize and bound multi-disciplinary uncertainties around the assessment of maize (Zea mays) production impacts using the CERES-Maize crop model in a climate-sensitive region with a variety of farming systems (Panama). Segunda coa (autumn) maize yield in Panama currently suffers occasionally from high water stress at the end of the growing season, however under future climate conditions warmer temperatures accelerate crop maturation and elevated CO (sub 2) concentrations improve water retention. This combination reduces end-of-season water stresses and eventually leads to small mean yield gains according to median projections, although accelerated maturation reduces yields in seasons with low water stresses. Calibrations of cultivar traits, soil profile, and fertilizer amounts are most important for representing baseline yields, however sensitivity to all management factors is reduced in an assessment of future yield changes (most dramatically for fertilizers), suggesting that yield changes may be more generalizable than absolute yields. Uncertainty around General Circulation Model (GCM)s' projected changes in rainfall gain in importance throughout the century, with yield changes strongly correlated with growing season rainfall totals. Climate changes are expected to be obscured by the large inter-annual variations in Panamanian climate that will continue to be the dominant influence on seasonal maize yield into the coming decades. The relatively high (A2) and low (B1) emissions scenarios show little difference in their impact on future maize yields until the end of the century. Uncertainties related to the sensitivity of CERES-Maize to carbon dioxide concentrations have a substantial influence on projected changes, and remain a significant obstacle to climate change impacts assessment. Finally, an investigation into the potential of simple statistical yield emulators based upon key climate variables characterizes the important uncertainties behind the selection of climate change metrics and their performance against more complex process-based crop model simulations, revealing a danger in relying only on long-term mean quantities for crop impact assessment.

Maize↗

NASA NTRS2015

Early Mars Climate Modeling and the Faint Young Sun Paradox.

Today Mars is a cold, dry, desert planet. Liquid water is not stable on its surface. There are no lakes, seas, or oceans, and precipitation falls as snowfall. Yet early in its history during the Noachian epoch, there is geological and mineralogical evidence that liquid water from rainfall flowed on its surface creating drainage systems, lakes, and - possibly - seas and oceans. More recent observations by Curiosity in Gale crater hint that such conditions may have persited into the Hesperian. The implication is that early Mars had a wamer climate than it does today as a result of a thicker atmosphere with a more powerful greenhouse effect capable of producing an active hydrological cycle with rainfall, runoff, and evaporation. Since Mariner 9 began accumulating such evidence, researchers have been trying to understand what kind of a climate system could have created greenhouse conditions favorable for liquid water. Unfortunately, the problem is not yet solved.

greenhouse gases↗

NASA NTRS2014

Laser Calibration of an Impact Disdrometer

A practical approach to developing an operational low-cost disdrometer hinges on implementing an effective in situ adaptive calibration strategy. This calibration strategy lowers the cost of the device and provides a method to guarantee continued automatic calibration. In previous work, a collocated tipping bucket rain gauge was utilized to provide a calibration signal to the disdrometer's digital signal processing software. Rainfall rate is proportional to the 11/3 moment of the drop size distribution (a 7/2 moment can also be assumed, depending on the choice of terminal velocity relationship). In the previous case, the disdrometer calibration was characterized and weighted to the 11/3 moment of the drop size distribution (DSD). Optical extinction by rainfall is proportional to the 2nd moment of the DSD. Using visible laser light as a means to focus and generate an auxiliary calibration signal, the adaptive calibration processing is significantly improved.

calibration↗

NASA NTRS2015

Combined Effect of El Nino Southern Oscillation and Atlantic Multidecadal Oscillation on Lake Chad Level Variability Region

In this study, the combined effect of the Atlantic Multidecadal Oscillation (AMO) and El Niño Southern Oscillation (ENSO) on the Lake Chad (LC) level variability is explored. Our results show that the lake level at the Bol monitoring station has a statistically significant correlation with precipitation (R2 = 0.6, at the 99.5% confidence level). The period between the late 1960s and early 1970s marked a turning point in the response of the regional rainfall to climatic drivers, thereby severely affecting the LC level. Our results also suggest that the negative impact of the cold phase of AMO on Sahel precipitation masks and supersedes the positive effect of La Niña in the early the 1970s. The drop in the size of LC level from 282.5 m in the early 1960s to about 278.1 m in 1983/1984 was the largest to occur within the period of study (1900-2010) and coincides with the combined cold phase of AMO and strong El Niño phase of ENSO. Further analyses show that the current warm phase of AMO and increasing La Niña episodes appear to be playing a major role in the increased precipitation in the Sahel region. The LC level is responding to this increase in precipitation by a gradual recovery, though it is still below the levels of the 1960s. This understanding of the AMO-ENSO-rainfall-LC level association will help in forecasting the impacts of similar combined episodes in the future. These findings also have implications for long-term water resources management in the LC region.

ENSO↗

NASA NTRS2016

The Influence of Volcanic Eruptions on the Climate of Tropical South America During the Last Millennium in an Isotope-Enabled General Circulation Model

Currently, little is known on how volcanic eruptions impact large-scale climate phenomena such as South American paleo-intertropical Convergence Zone (ITCZ) position and summer monsoon behavior. In this paper, an analysis of observations and model simulations is employed to assess the influence of large volcanic eruptions on the climate of tropical South America. This problem is first considered for historically recent volcanic episodes for which more observations are available but where fewer events exist and the confounding effects of El Niño-Southern Oscillation (ENSO) lead to inconclusive interpretation of the impact of volcanic eruptions at the continental scale. Therefore, we also examine a greater number of reconstructed volcanic events for the period 850 CE to present that are incorporated into the NASA GISS ModelE2-R simulation of the last millennium. An advantage of this model is its ability to explicitly track water isotopologues throughout the hydrologic cycle and simulating the isotopic imprint following a large eruption. This effectively removes a degree of uncertainty associated with error-prone conversion of isotopic signals into climate variables, and allows for a direct comparison between GISS simulations and paleoclimate proxy records. Our analysis reveals that both precipitation and oxygen isotope variability respond with a distinct seasonal and spatial structure across tropical South America following an eruption. During austral winter, the heavy oxygen isotope in precipitation is enriched, likely due to reduced moisture convergence in the ITCZ domain and reduced rainfall over northern South America. During austral summer, however, more negative values of the precipitation isotopic composition are simulated over Amazonia, despite reductions in rainfall, suggesting that the isotopic response is not a simple function of the "amount effect". During the South American monsoon season, the amplitude of the temperature response to volcanic forcing is larger than the rather weak and spatially less coherent precipitation signal, complicating the isotopic response to changes in the hydrologic cycle.

Colose, Christopher M.↗

NASA NTRS2016

Supplement of: The Influence of Volcanic Eruptions on the Climate of Tropical South America During the Last Millennium in an Isotope-Enabled General Circulation Model

Currently, little is known on how volcanic eruptions impact large-scale climate phenomena such as South American paleo-intertropical Convergence Zone (ITCZ) position and summer monsoon behavior. In this paper, an analysis of observations and model simulations is employed to assess the influence of large volcanic eruptions on the climate of tropical South America. This problem is first considered for historically recent volcanic episodes for which more observations are available but where fewer events exist and the confounding effects of El NioSouthern Oscillation (ENSO) lead to inconclusive interpretation of the impact of volcanic eruptions at the continental scale. Therefore, we also examine a greater number of reconstructed volcanic events for the period 850CE to present that are incorporated into the NASA GISS ModelE2-R simulation of the last millennium.An advantage of this model is its ability to explicitly track water isotopologues throughout the hydrologic cycle and simulating the isotopic imprint following a large eruption. This effectively removes a degree of uncertainty associated with error-prone conversion of isotopic signals into climate variables, and allows for a direct comparison between GISS simulations and paleoclimate proxy records.Our analysis reveals that both precipitation and oxygen isotope variability respond with a distinct seasonal and spatial structure across tropical South America following an eruption. During austral winter, the heavy oxygen isotope in precipitation is enriched, likely due to reduced moisture convergence in the ITCZ domain and reduced rainfall over northern South America. During austral summer, however, more negative values of the precipitation isotopic composition are simulated over Amazonia, despite reductions in rainfall, suggesting that the isotopic response is not a simple function of the amount effect. During the South American monsoon season, the amplitude of the temperature response to volcanic forcing is larger than the rather weak and spatially less coherent precipitation signal, complicating the isotopic response to changes in the hydrologic cycle.

Colose, Christopher↗

NASA NTRS2016

Seasonal Variation of Total Mercury Burden in the American Alligator (Alligator Mississippiensis) at Merritt Island National Wildlife Refuge (MINWR), Florida

Seasonal variation of mercury (Hg) is not well studied in free-ranging wildlife. Atmospheric deposition patterns of Hg have been studied in detail and have been modeled for both global and specific locations with great accuracy and correlates to environment impact. However, monitoring these trends in wildlife is complicated due to local environmental parameters (e.g., rainfall, humidity, pH, bacterial composition) that can affect the transformation of atmospheric Hg to the biologically available forms. Here, we utilized an abundant and healthy population of American alligators (Alligator mississippiensis) at Merritt Island National Wildlife Refuge (MINWR), FL, and assessed Hg burden in whole blood samples over a span of 7 years (2007 2014; n 174) in an effort to assess seasonal variation of total [Hg]. While the majority of this population is assumed healthy, 18 individuals with low body mass indices (BMI, defined in this study) were captured throughout the 7 year sampling period. These individual alligators exhibited [Hg] that were not consistent with the observed overall seasonal [Hg] variation, and were statistically different from the healthy population of alligators. The alligators with low BMI had elevated concentrations of Hg compared to their age/sex/season matched counterparts with normal BMI. Statistically significant differences were found between the winter and spring seasons for animals with normal BMI. The data in this report supports the conclusion that organismal total [Hg] do fluctuate directly with seasonal deposition rates as well as other seasonal environmental parameters, such as average rainfall and prevailing wind direction. This study highlights the unique environment of MINWR to permit annual assessment of apex predators, such as the American alligator, to determine detailed environmental impact of contaminants of concern.

Hg↗

NASA NTRS2016

Identifying and Analyzing Uncertainty Structures in the TRMM Microwave Imager Precipitation Product over Tropical Ocean Basins

Despite continuous improvements in microwave sensors and retrieval algorithms, our understanding of precipitation uncertainty is quite limited, due primarily to inconsistent findings in studies that compare satellite estimates to in situ observations over different parts of the world. This study seeks to characterize the temporal and spatial properties of uncertainty in the Tropical Rainfall Measuring Mission Microwave Imager surface rainfall product over tropical ocean basins. Two uncertainty analysis frameworks are introduced to qualitatively evaluate the properties of uncertainty under a hierarchy of spatiotemporal data resolutions. The first framework (i.e. 'climate method') demonstrates that, apart from random errors and regionally dependent biases, a large component of the overall precipitation uncertainty is manifested in cyclical patterns that are closely related to large-scale atmospheric modes of variability. By estimating the magnitudes of major uncertainty sources independently, the climate method is able to explain 45-88% of the monthly uncertainty variability. The percentage is largely resolution dependent (with the lowest percentage explained associated with a 1 deg x 1 deg spatial/1 month temporal resolution, and highest associated with a 3 deg x 3 deg spatial/3 month temporal resolution). The second framework (i.e. 'weather method') explains regional mean precipitation uncertainty as a summation of uncertainties associated with individual precipitation systems. By further assuming that self-similar recurring precipitation systems yield qualitatively comparable precipitation uncertainties, the weather method can consistently resolve about 50 % of the daily uncertainty variability, with only limited dependence on the regions of interest.

Climate↗

NASA NTRS2016

Evaluating ESA CCI Soil Moisture in East Africa

To assess growing season conditions where ground based observations are limited or unavailable, food security and agricultural drought monitoring analysts rely on publicly available remotely sensed rainfall and vegetation greenness. There are also remotely sensed soil moisture observations from missions like the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and NASAs Soil Moisture Active Passive (SMAP), however these time series are still too short to conduct studies that demonstrate the utility of these data for operational applications, or to provide historical context for extreme wet or dry events. To promote the use of remotely sensed soil moisture in agricultural drought and food security monitoring, we use East Africa as a case study to evaluate the quality of a 30+ year time series of merged active-passive microwave soil moisture from the ESA Climate Change Initiative (CCI-SM). Compared to the Normalized Difference Vegetation index (NDVI) and modeled soil moisture products, we found substantial spatial and temporal gaps in the early part of the CCI-SM record, with adequate data coverage beginning in 1992. From this point forward, growing season CCI-SM anomalies were well correlated (R greater than 0.5) with modeled, seasonal soil moisture, and in some regions, NDVI. We use correlation analysis and qualitative comparisons at seasonal time scales to show that remotely sensed soil moisture can add information to a convergence of evidence framework that traditionally relies on rainfall and NDVI in moderately vegetated regions.

Amy McNally↗

NASA NTRS2017

So, How Much of the Earth's Surface Is Covered by Rain Gauges?

The measurement of global precipitation, both rainfall and snowfall, is critical to a wide range of users and applications. Rain gauges are indispensable in the measurement of precipitation, remaining the de facto standard for precipitation information across Earths surface for hydrometeorological purposes. However, their distribution across the globe is limited: over land their distribution and density is variable, while over oceans very few gauges exist and where measurements are made, they may not adequately reflect the rainfall amounts of the broader area. Critically, the number of gauges available, or appropriate for a particular study, varies greatly across the Earth owing to temporal sampling resolutions, periods of operation, data latency, and data access. Numbers of gauges range from a few thousand available in near real time to about 100,000 for all official gauges, and to possibly hundreds of thousands if all possible gauges are included. Gauges routinely used in the generation of global precipitation products cover an equivalent area of between about 250 and 3,000 sq m. For comparison, the center circle of a soccer pitch or tennis court is about 260 sq m. Although each gauge should represent more than just the gauge orifice, autocorrelation distances of precipitation vary greatly with regime and the integration period. Assuming each Global Precipitation Climatology Centre (GPCC) available gauge is independent and represents a surrounding area of 5-km radius, this represents only about 1% of Earths surface. The situation is further confounded for snowfall, which has a greater measurement uncertainty.

Rain gauge↗

NASA NTRS2017

Precipitation Characteristics in Tropical Africa Using Satellite and In-Situ Observations

Tropical Africa receives nearly all its precipitation as a result of convection. The characteristics of rain-producing systems in this region, despite their crucial role in regional and global circulation, have not been well-understood. This is mainly due to the lack of in situ observations. Here, we have used precipitation records from the Trans-African Hydro-Meteorological Observatory (TAHMO) to improve our knowledge about the rainfall systems in the region, and to validate the recently-released IMERG precipitation product. The high temporal resolution of the gauge data has allowed us to identify three classes of rain events based on their duration and intensity. The contribution of each class to the total rainfall and the favorable surface atmospheric conditions for each class have been examined. As IMERG aims to continue the legacy of its predecessor, TMPA, and provide higher resolution data, continent-wide comparisons are made between these two products. IMERG, due to its improved temporal resolution, shows some advantages over TMPA in capturing the diurnal cycle and propagation of the meso-scale convective systems. However, the performance of the two satellite-based products varies by season, region and the evaluation statistics. The results of this study serve as a basis for our ongoing work on the impacts of biomass burning on precipitation processes in Africa.

TMPA↗

NASA NTRS2017

An Integrated Examination of AMSR2 Products over Ocean

Integrated processing and analysis are presented for oceanic retrievals of precipitation, sea ice concentration, columnar water vapor and cloud water, sea surface temperature, and near surface wind from the advanced microwave scanning radiometer-2 (AMSR2) sensor. By developing a common algorithmic framework and permitting iterative interaction between historically separate science algorithms, ambiguous and contradictory retrieval results are minimized. The integration also serves to improve each algorithm individually, decreasing reliance on ancillary datasets. Case studies are presented that exemplify both ongoing challenges for these retrievals and potential research uses of such an integrated satellite product. Two cases are presented each for precipitation at high latitudes and marginal sea ice detection, with analysis supplemented by satellite data from CloudSat profiles and Himawari-8 imagery. Detection and retrieval of snowfall remains a challenge, while light rainfall detection can be aided by a variational algorithm. Sea ice concentrations below 20% cause disagreements, but the algorithms otherwise agree well on the sea ice edge. Potential mitigation strategies for ambiguous areas of light rainfall and marginal sea ice are discussed. The analysis demonstrates potential avenues for future algorithm development, but also some physical limitations of remote sensing with the AMSR2 frequencies.

variational methods↗

NASA NTRS2018

The Next-Generation Goddard Convective-Stratiform Heating Algorithm: New Tropical and Warm-Season Retrievals for GPM

The Goddard convective-stratiform heating (CSH) algorithm, used to estimate cloud heating in support of the Tropical Rainfall Measuring Mission (TRMM), is upgraded in support of the Global Precipitation Measurement (GPM) mission. The algorithm's lookup tables (LUTs) are revised using new and additional cloud-resolving model (CRM) simulations from the Goddard Cumulus Ensemble (GCE) model, producing smoother heating patterns that span a wider range of intensities because of the increased sampling and finer GPM product grid. Low-level stratiform cooling rates are reduced in the land LUTs for a given rain intensity because of the rain evaporation correction in the new four-class ice (4ICE) scheme. Additional criteria, namely, echo-top heights and low-level reflectivity gradients, are tested for the selection of heating profiles. Those resulting LUTs show greater and more precise variation in their depth of heating as well as a tendency for stronger cooling and heating rates when low-level dBZ values decrease toward the surface. Comparisons versus TRMM for a 3-month period show much more low-level heating in the GPM retrievals because of increased detection of shallow convection, while upper-level heating patterns remain similar. The use of echo tops and low-level reflectivity gradients greatly reduces midlevel heating from ~2 to 5 km in the mean GPM heating profile, resulting in a more top-heavy profile like TRMM versus a more bottom-heavy profile with much more midlevel heating. Integrated latent heating rates are much better balanced versus surface rainfall for the GPM retrievals using the additional selection criteria with an overall bias of +4.3%.

Lang, Stephen E.↗

NASA NTRS2018

Latent Heating from TRMM and GPM Measurement

The Goddard Convective-Stratiform Heating (CSH) algorithm, used to estimate cloud heating in support of the Tropical Rainfall Measuring Mission (TRMM), is upgraded in support of the Global Precipitation Measurement mission (GPM). The algorithm is required to use look-uptables (LUTs) from cloud-resolving model (CRM) simulations from the Goddard Cumulus Ensemble model (GCE). This paper will present the heating retrievals from the Goddard CSH algorithm in the TRMM and GPM using precipitation products (rainfall, radar reflectivity).

Latent Heating↗

NASA NTRS2018

Satellite Observations and Modeling to Understand the Lower Mekong River Basin Streamflow Variability

In this work, we have used the Soil & Water Assessment Tool (SWAT) to examine streamflow variability of the Lower Mekong River Basin (LMRB) associated with changes in the Upper Mekong River Basin (UMRB) inflows. Two hypothetical experiments were formulated and evaluated for the LMRB, where we conducted runoff simulations with multiple inflow changes that include upstream runoff yield increase and decrease scenarios. Streamflow variability of the LMRB was quantified by two streamflow metrics that explain flow variability and predictability, and high flow disturbance. The model experiments were performed for the Lower Mekong River Basin with identical climate, soil, and other watershed characteristics data. Remote sensing precipitation (Tropical Rainfall Measurement Mission, TRMM, and Global Precipitation Measurement mission, GPM), meteorological data as well as spatial data that include a digital elevation model, newly developed soil information (Harmonized World Soil Database, HWSD), and land use and land cover were processed as input to the LMRB model simulations. Observed daily streamflow data along the Lower Mekong River from Chiang Sean, Thailand to Kratie, Cambodia were used for calibration and validation. Our work results suggest that the Lower Mekong River streamflow is highly variable and has a low predictability (Colwell index of about 32%). We found that releasing more water from upstream Mekong during rainfall months by 30% would result in a reduction in the Lower Mekong streamflow predictability by about 21%. This reduction in predictability is mainly attributed to a decrease in the Contingency index. Our work shows that the ability to predict floods/droughts at the Lower Mekong River would be reduced if there is any anticipated change (i.e., increase/decrease) from UMRB releases. Our results also show that releasing more flows from the upstream Mekong would also affect flood duration and the frequency of flood occurrences downstream. The results of this work thus help to quantify the sensitivity of streamflow variability at the Lower Mekong River Basin to upstream anthropogenic changes.

Streamflow Predictability↗

NASA NTRS2018

July 2018 Mid-Atlantic Atmospheric River and Extreme Precipitation Event Captured by MERRA-2

Despite starting off the month with hardly any precipitation, July 2018 turned out to be one of the wettest on record in the Baltimore/Washington D.C. area. Daily rainfall records were demolished as an entire month's worth of precipitation fell in a matter of days and flash flood warnings covered the region. Beginning on July 21, 2018, an atmospheric river, or a narrow stream of enhanced water vapor transport, positioned itself over the region, bringing gray skies and precipitation for days. This was captured by GMAO's Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), and given the nearly 40-year record of MERRA-2, can be placed in the context of past events and the overall climate for the region during July. Not only was the multi-day rainfall out of character, but large-scale features throughout July differed from climatology and there were even bigger differences in the state of the atmosphere between the first and second halves of July 2018.

Collow, Allie↗

NASA NTRS2016

Convective Influence on the Lower Stratospheric Water Vapor in the Boreal Summer Asian Monsoon Region

Processes maintaining the localized maxima in lower stratospheric watervapor over the boreal summer Asian monsoon region are investigated usingtrajectory and cloud models that resolve the detailed cloudmicrophysical processes, with observation-based convection and radiationschemes. We examine the impact of convective influence along parceltrajectories on cloud formation and dehydration by tracing thetrajectories through time-dependent fields of convective cloud topheights estimated from global rainfall and geostationary brightnesstemperatures. Parameters such as the rainfall threshold used foridentification of deep convection are derived by comparison with theCloudSat deep convective cloud top product as enhanced by colocatedCALIOP measurements. The simulated water vapor field at the 100 hPalevel and cloud occurrence frequencies in the tropical tropopause layer(TTL) are constrained by corresponding observations from MLS andCALIPSO, respectively. The observed maximum in the 100 hPa level watervapor field over the Asian monsoon region is only present in thesimulation with convective influence, indicating the importance ofconvective hydration for the summertime water vapor distribution.Convection moistens the 100 hPa level over the Asian monsoon by 1 ppmv,where 75 of this moistening is due to convection occurring locallywithin the monsoon region. Convection also increases the cloudoccurrence frequency in the TTL over the southern sector of the Asianmonsoon anticyclone by 20. Parcels are convectively hydrated in thesoutheastern sector of the anticyclone, transported westward by theanticyclonic circulation, and dehydrated in the southwestern sector. Therelative importance of extreme convective events that inject ice andwater vapor near or above the tropopause will also be examined.

convection↗

NASA NTRS2017

Increasing Resiliency to Extreme Weather

We work at NASA's Goddard Institute for Space Studies, integrating the agency's satellite imagery and projections of extreme weather events into urban planning. In recent weeks, we have watched as Christian's hometown, Houston, has been ransacked by historic rainfall and flooding and Hurricane Irma has battered the U.S. Virgin Islands, Puerto Rico and Florida. Then, Hurricane Maria devastated Puerto Rico leaving millions of people without power. Sea-level rise, storm surge, warm ocean temperatures, and extreme rainfall interacted to exacerbate the damages incurred by Hurricanes Harvey, Irma, and Maria. Coastal flooding combined with inland flooding to wreak extraordinary havoc.

Rosenzweig, Cynthia↗